Philadelphia College of Osteopathic Medicine
DigitalCommons@PCOM
PCOM Psychology Dissertations Student Dissertations, Theses and Papers
2010
Integrity of Neuropsychological Processes in
Children with Attention-deficit/hyperactivity
Disorder and Comorbid Conditions
Julie N. Henzel
Philadelphia College of Osteopathic Medicine, juliehen@pcom.edu
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Recommended Citation
Henzel, Julie N., "Integrity of Neuropsychological Processes in Children with Attention-deficit/hyperactivity Disorder and Comorbid Conditions" (2010).PCOM Psychology Dissertations.Paper 160.
Philadelphia College of Osteopathic Medicine Department of Psychology
INTEGRITY OF NEUROPSYCHOLOGICAL PROCESSES IN CHILDREN
WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER AND
COMORBID CONDITIONS
By Julie N. Henzel
Submitted in Partial Fulfillment of the Requirements of the Degree of Doctor of Psychology
Committee Members' Signatures:
James Brad Hale, Ph.D., Chairperson
Lisa Hain, Psy.D.
George McCloskey, Ph.D.
Acknowledgments
To my dissertation committee, James B. Hale, Ph.D., George McCloskey, Ph.D., and Lisa Hain, Psy.D. for their patience, dedication, and support. Thank you for sharing your invaluable knowledge and for challenging me to become a better scholar and practitioner.
A special thank you to Dr. Hale who involved me in multiple scholarly projects and publications prior to completing this dissertation. These
opportunities greatly enhanced my scholarly thinking and writing skills.
Additionally, my clinical skills would not be what they are today without having had these opportunities.
To my parents, Jeffrey and Jacqueline Taylor, who taught me that I can accomplish anything through hard work and persistence. Also, thank you for instilling high academic aspirations in me from a young age.
To my husband, Kevin Henzel, for his immeasurable patience, love, and support throughout this process. Thank you for believing in my goals and dreams as if they were your own.
For the staff at Child and Adolescent Behavioral Health in Canton, Ohio. This study would not be possible without your assistance in the data collection process. Thank you for your willingness to share information, your professional guidance, and for all of the time you cheerfully volunteered to assist me with obtaining my data sample.
ADHD AND NEUROPSYCHOLOGY iv
Finally, thank you to Lisa Hain, Psy.D. and Allison Evans, Ph.D., for contributing data to this study and for meeting my tight timelines. I have enjoyed collaborating with you on this professional endeavor and look forward to working with you on future projects.
Abstract
This study investigated the neuropsychological and behavioral profiles seen in children diagnosed with ADHD inattentive type (IA), inattentive type plus an internalizing disorder (IA + INT), combined type (CT), and combined type plus an externalizing disorder (CT + EXT). Subjects were 63 unmedicated children aged 6 to 16 who had been assessed with the Wechsler Intelligence Scale for Children–Fourth Edition (WISC–IV), Conners’ Continuous Performance Test-Second Edition (CPT–II), and the Child Behavior Checklist (CBCL). Group differences were found for the WISC–IV Digits Backward subtest (IA + INT <IA), various CPT–II consistency measures (CT + EXT>IA and IA + INT), and externalizing behavior scales on the CBCL and TRF (IA + INT>IA, CT + EXT > CT). Forced-entry discriminant analyses were used to investigate whether the neuropsychological and behavioral measures could accurately predict group membership and to more generally evaluate the utility of a combined
neuropsychological/behavioral approach in ADHD assessment. Combined methods resulted in correct classification rates of 88.9% and even 100% when the Teacher Report Form (TRF) was included, as compared to 68.3% to 71.4% for separate approaches. Results support meaningful distinctions among ADHD IA, IA + INT, CT, and CT + EXT groups, and the utility of the WISC–IV, CPT–II, CBCL, and TRF in differentiating these groups. Results further illustrate the
ADHD AND NEUROPSYCHOLOGY vi
heterogeneous nature of ADHD and the value of using a combined neuropsychological/behavioral approach in ADHD assessment.
Table of Contents Abstract ...v Chapter 1 Introduction ...1 Assessment of ADHD...4
Limitations of Behaviorally Based ADHD Assessment...5
A New Approach to ADHD Assessment...11
Chapter 2 Literature Review...14
ADHD and Common Comorbid Conditions ...14
Oppositional Defiant Disorder/Conduct Disorder ...14
Anxiety/Mood Disorders ...15
Neuropsychology of ADHD ...17
Neuropsychology of Common ADHD Comorbidities ...22
ADHD and Neuropsychological Processes ...24
Auditory-Verbal...24
Visuospatial...26
Processing Speed ...28
Working Memory...30
Sustained Attention...31
ADHD AND NEUROPSYCHOLOGY viii
Research Problem and Limitations of Past Research ...36
Chapter 3 Method ...40
Subjects...40
Instrumentation ...42
Wechsler Intelligence Scale for Children-Fourth Edition ...42
Conners’ Continuous Performance Test-Second Edition ...47
Achenbach Child Behavior Checklist...50
Procedure ...52
Analysis...53
Chapter 4 Results...56
Descriptive Statistics...56
Exploration of the ADHD Subgroup Profiles...70
Neuropsychological and Behavioral Characteristics of the Inattentive Type Group ...81
Neuropsychological and Behavioral Characteristics of the Inattentive Neuropsychological and Behavioral Characteristics of the Type Plus Internalizing Disorders Group ...85
Neuropsychological and Behavioral Characteristics of the Combined
Type Plus Externalizing Disorders Group ...92
Discriminant Analysis of the ADHD Subgroups...95
Comparing Neuropsychological and Behavioral Approaches in ADHD Diagnosis...99
Chapter 5 Discussion.. ...102
Neuropsychological Implications ...110
Limitations of Present Study...114
Directions for Future Research ...116
References...119
ADHD AND NEUROPSYCHOLOGY x
List of Tables Table 1. Demographic Variables by ADHD Clinical Subtype (Sample A)…….58
Table 2. Means, Standard Deviations, and Ranges for Sample B Across WISC-IV Variables...63
Table 3. Means, Standard Deviations, and Ranges for Sample B Across Table 4. Means, Standard Deviations, and Ranges for Sample B Across Table 5. Means, Standard Deviations, and Ranges for Sample C Across Teacher Table 6. Means, Standard Deviations, and Significance Levels for WISC-IV Table 7. Means, Standard Deviations, and Significance Levels for CPT-II Table 8. Means, Standard Deviations, and Significance Levels for Parent Table 9. Means, Standard Deviations, and Significance Levels for Teacher Table 10. Pooled Within Group Correlations With Standardized Canonical Discriminant Functions for Cognitive/Neuropsychological/ CPT-II Variables...65
Parent Reported Behavioral Variables...67
Reported Behavioral Variables...69
Variables Across ADHD Subgroups (Sample B)...71
Variables Across ADHD Subgroups (Sample B)...74
Reported Behavioral Variables Across ADHD Subgroups (Sample B)...77
Reported Behavioral Variables across ADHD Subgroups (Sample C)...79
List of Figures
Figure 1. Cognitive Profiles for ADHD Subgroups...73
Figure 2. Attention Profiles for ADHD Subgroups...78
Figure 3. Parent Behavioral Report Profiles for ADHD Subgroups...80
ADHD AND NEUROPSYCHOLOGY
Chapter 1 Introduction
Attention-deficit hyperactivity disorder (ADHD) is a common referral concern encountered by psychologists in both clinical and school practice. It is estimated that 8.7% of U.S. children ages 8 to 15, or 2.4 million children meet diagnostic criteria for ADHD (Froehlich et al. 2007), with similar prevalence rates found across other developed countries (Faraone, Sergeant, Gillberg, &
Biederman, 2003). ADHD is primarily a genetic disorder, with twin studies suggesting a heritability rate of 76% (Faraone et al. 2005). Risk factors include maternal smoking during pregnancy (Mich, Biederman, Faraone, Sayer, & Kleinman, 2002), low birth weight (Nigg & Breslau, 2007), and
pregnancy/delivery complications (Sprich-Buckminster, Biederman, & Milberger, 1993).
Characterized by a significant impairment in inattention and/or
hyperactivity-impulsivity that is present in at least two settings such as home and school, ADHD can have negative implications for various aspects of a child’s life (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; DSM–IV–TR; American Psychiatric Association; APA, 2000). Individuals with ADHD demonstrate self-regulatory difficulties in everyday life that include activation (organizing tasks, estimating time, starting tasks, and prioritizing), focusing (sustaining focus and shifting focus among tasks), effort
(sustaining effort, processing speed, and regulating alertness), emotion (handling frustration and regulating emotions), memory (accessing previously learned information and working memory), and action (monitoring/regulating actions) (Brown, 2009). Furthermore, these difficulties often extend to cognitive functioning, academic achievement, (DuPaul, McGoey, Eckert, & VanBrakle, 2001), peer relationships (Hoza, 2007), self-esteem, and psychological well-being (Edbom, Granlund, Lichtenstein, & Larsson, 2008).
For the majority of children diagnosed with ADHD, this condition will persist into adulthood and may continue to have negative consequences on their lives if not managed appropriately (Barkley, 2005; Barkley, Murphy, & Fischer, 2008; Spencer, Biederman, & Mick, 2007). Long-term outcome studies suggest that individuals with ADHD are more likely to drop out of high school (32% to 40%), fail to complete college (5% to 10%), engage in antisocial activities (40% to 50%), and to underperform at work (70% to 80%) (Barkley et al., 2002). This population is also more prone to engage in unhealthy or unsafe activities, such as excessive speeding while driving and tobacco/illicit drug use (Barkley et al., 2002). Approximately 18% to 25% will go on to receive a personality disorder diagnosis as adults (Barkley et al., 2002).
Three main subtypes of ADHD are currently recognized in the DSM–IV– TR (APA, 2000). These include predominantly inattentive type (ADHD-IA), predominantly hyperactive-impulsive Type (ADHD-HI), and combined type
ADHD AND NEUROPSYCHOLOGY 3
(ADHD-CT). The DSM–IV–TR also allows for the diagnosis of ADHD Not Otherwise Specified (ADHD NOS) when an individual’s symptoms do not completely meet criteria. Twenty percent to 30% of children with ADHD have predominately inattentive subtype (Spencer et al., 2007), which is characterized by behavioral symptoms such as failing to give close attention to details or making careless errors in work, difficulty sustaining attention in tasks or activities, and becoming easily distracted by extraneous stimuli (APA, 2000). Fewer than 15% of children with ADHD are within the predominantly
hyperactive-impulsive category (Spencer, 2007), which is represented by behavioral symptoms such as difficulty awaiting one’s turn, sitting still, and staying seated at appropriate times. The majority of children are in the ADHD-CT category (50% to 75%; Spencer et al., 2007), which is associated with symptoms from both the inattentive and hyperactive-impulsive categories (see APA, 2000). A child must demonstrate at least six of nine behavioral symptoms from the inattentive and/or hyperactive-impulsive categories in two or more settings in order to qualify for an ADHD diagnosis (APA, 2002). Additionally, some symptoms must have been present prior to the age of 7.
In 77% of cases, ADHD is comorbid with at least one other condition (Biederman, Faraone, & Lapey, 1992), thus making comorbidity the rule rather than the exception (Ollendick, Jarrett, Grills-Taquechel, Hovey, & Wolff, 2008). Rates range from 3% to 51% for concurrent internalizing disorders and 43% to
93% for externalizing disorders (Ollendick et al., 2008). Common comorbid psychiatric conditions seen in ADHD include other disruptive behavior disorders (25% to 40%), anxiety disorders (30%), mood disorders (10% to 30%), and tic disorders (6%) (National Resource Center on ADHD, 2003). Learning disabilities also co-occur in children with ADHD at a rate of 31% (DuPaul & Stoner, 2003), with reading (8% to 39%), math (12% to 30%), and spelling (12% to 27%) problems frequently reported (Barkley, 2005). Internalizing disorders, such as depression or anxiety, occur at similar rates across ADHD subtypes, while externalizing disorders tend to be more common in ADHD-HI or ADHD-CT (Elia, Ambrosini, & Berrettini, 2008; Jensen, Martin, & Cantwell, 1997; Power, Costigan, Eiraldi, & Leff, 2004). Girls with ADHD tend to manifest comorbid internalizing disorders, whereas boys are more prone to externalizing disorders, such as oppositional defiant disorder (ODD) and conduct disorder (CD) (Gershon & Gershon, 2002). Comorbid learning disabilities tend to be more common in children with ADHD-IA (Marshall, Hynd, Handwerk, & Hall, 1997). A high degree of similarity between the behavioral expressions of conditions such as anxiety or ODD with ADHD further complicates the diagnostic picture when assessing a child for suspected ADHD.
Assessment of ADHD.
Traditional assessment of ADHD is largely behaviorally-based and relies heavily on teacher and parental reports of behavior (see Barkley, 1997a). ADHD
ADHD AND NEUROPSYCHOLOGY 5
assessments typically include a parent interview, teacher interview, observations of behavior, and standardized child behavior checklists. Demographic
information, information on presenting concerns, and developmental, medical, school, and family histories are gathered during the course of the parent interview. The clinician also typically inquires about the presence of symptoms of other major childhood developmental and psychiatric conditions. This can be
accomplished through semistructured or unstructured formats, but comparisons should be made to DSM behavioral criteria for ADHD (American Academy of Pediatrics; AAP, 2000; Barkley, 1997a). Standardized child behavior checklists designed to assess ADHD provide a means of quantifying the degree to which a child’s behavior deviates from typical same-aged peers and can provide a means of gathering information from observers of the child’s behavior who can not be directly interviewed. In addition to narrow-band rating scales that are primarily designed to measure ADHD, clinicians also frequently use broad-band rating scales to assess for the presence of comorbid conditions (AAP, 2000).
Limitations of behaviorally based ADHD assessment.
Important limitations exist in a behavioral approach to ADHD assessment that complicate the differential diagnosis process. The techniques of gathering information from multiple informants in the form of interviews or psychosocial rating scales are considered best practice for ADHD assessment (e.g. American Academy of Pediatrics; AAP, 2000; Barkley, 1997). However, discordance
among informants of a child’s behavior is common (Angtrop, Roeyers, Oosterlaan, & Van Oost, 2002; Bird, Gould, & Staghezza, 1992; Grills & Ollendick, 2002), with correlations only reaching .27 between parents and teachers, .25 between parent and child self-report, and .20 between teacher and child self-report (Achenbach, McConaughy, & Howell, 1987). Additionally, psychosocial rating scales have shown limited utility for discriminating among disorders with similar symptom patterns (Hale, How, DeWitt, & Coury, 2001; Mahone et al., 2002; Sullivan & Riccio, 2007). Factors such as altered
environmental demands and differences in behavioral expectations/tolerances of a child’s behavior may account for discordance between parents and teachers (Burns, Walsh, & Gomez, 2003; Konold, Walthall, & Pianta, 2004).
Discrepancies between child and adult ratings often arise when an internalizing disorder is present. While adults are generally regarded as more valid reporters for externalizing disorders with overt symptoms such as ADHD and oppositional defiant disorder (ODD) (Bird et al., 1992), a child’s ratings may be more relevant for internalizing disorders that hinge on subjective distress such as generalized anxiety disorder (GAD) or depression (Masi, Mucci, Favilla, Romano, & Poli, 1999).
Because there is much overlap between the symptoms of ADHD and other psychiatric conditions, accurately diagnosing ADHD requires an understanding of the behavioral patterns of numerous disorders (Reddy & Hale, 2007). Inattention,
ADHD AND NEUROPSYCHOLOGY 7
a hallmark behavioral symptom of ADHD (see APA, 2002), can be attributed to at least 38 different conditions (Goodman & Poillion, 1992). Disorders where a disruption of attention is commonly seen include learning disabilities, pervasive developmental disorders, auditory processing disorders, anxiety disorders, and mood disorders (Reddy & Hale, 2007).
In a behavioral approach, there is a tendency to view the symptom of inattention as a unitary concept (i.e. whether or not the child has difficulty sustaining attention). However, neuropsychology suggests that inattention is indeed multifaceted (Baron, 2004; Miller, 2007; Miller & Hale, 2007, Mirsky, Bruno, Duncan, Ahearn, & Kellam, 1991). Forms of attention important to consider include shifting (reallocating attention from one thing to another; Mirsky et al., 1991), divided (multitasking or attending to multiple things at once; Baron, 2004), selective/focused (maintaining focus in the presence of background
distractions; Baron, 2004), sustained (staying on task over longer periods of time; Mirsky et al., 1991), and attentional capacity (the use of attention for memory purposes; Miller, 2007). An additional model of attention includes orienting
(attending to location of sensory information), detecting (reporting the presence of a target for conscious processing), and alerting (preparing for the processing of a priority event) (Posner & Petersen, 1990).
Practitioners should also consider whether a child’s distraction or
or external (i.e., caused by stimuli in the external environment) (Miller, 2007; Reddy & Hale, 2007). For example, a child with an anxiety disorder may become distracted due to replaying a recent fight with a friend or worrying about an upcoming test. In contrast, a child with ADHD might be distracted by materials in his desk or noise outside the classroom.
The clinical criteria as outlined in the DSM–IV–TR have also been a source of debate in terms of gender equity and threshold level. ADHD is diagnosed in boys 3 times more often than in girls (Barkley, 2005; Elia,
Ambrosini, & Berretini, 2008), and boys are 5 to 9 times more likely to present to clinics with ADHD symptoms than girls (Barkley, 2005). However, the DSM– IV–TR does not currently account for differences in male/female symptom
expression patterns, which may partially explain why males are disproportionally diagnosed with this condition. It has been shown that parents and teachers typically report lower levels of ADHD symptoms in females than males (DuPaul, 1991; Gershon & Gershon, 2002), and as Barkley (2005) points out, the DSM–IV
ADHD threshold level was set through studies that primarily investigated this condition in boys (also see Lahey et al., 1994). Barkley (2005) suggests that the ADHD clinical criteria may be unfairly high to females, for females must essentially demonstrate a higher degree of impairment in order to qualify for a diagnosis.
ADHD AND NEUROPSYCHOLOGY 9
It has also been questioned whether the current threshold level is appropriate for identifying children who truly require treatment for ADHD symptomatology as well as specifying subtype (Barkley, 2005; Hale & Fiorello, 2004). Children who fall below the 6-symptom criteria (APA, 2000) are less likely to receive treatment, yet they may still show significant impairment (Elk, Fernell, Westerlund, Holmberg, Olsson, & Gillberg, 2007; Scahill et al., 1999). Additionally, ADHD subtypes, as currently defined by symptom counts are not always clear and may not be stable constructs throughout a child’s life. In the case of children initially diagnosed with ADHD-HI, many may later meet criteria for inattentive or combined types, given that hyperactive symptoms have been shown to decrease as a child ages (Barkley, 2005; Lahey, Pelham, Loney, Lee, & Willcutt, 2005). Rather than actually shifting subtypes, it has been proposed that children initially diagnosed with ADHD-HI may have an earlier developmental stage of ADHD-CT or have a milder version of CT (Barkley, 2005). Though children initially diagnosed as ADHD-HI may also meet criteria for IA later in life, they tend to retain their inhibitory deficits, which are not present in children with true ADHD-IA (Barkley, 2005).
Research has suggested that two additional distinct subtypes of ADHD may also exist, which are not currently recognized by the DSM–IV–TR. These include ADHD plus externalizing disorders such as oppositional defiant disorder (ODD) or conduct disorder (CD), as well as ADHD plus internalizing disorders,
such as anxiety and depression (Angold, Costello, & Erkanli, 1999; Barkley, 2005; Jensen et al., 2001; Stefanatos & Baron, 2007). ADHD plus internalizing disorders as an additional subtype is often discussed in the context of children who manifest characteristics of sluggish cognitive tempo (SCT) (Barkley, 2005).
Comorbid ODD or CD is most frequently seen in children with ADHD-CT or ADHD-HI (Acosta, et al., 2008; Elia et al., 2008). ADHD plus ODD or CD may represent a more severe form of ADHD (Barkley, 2005), which is characterized by increased impulsivity (Lynam, 1998), physical aggression (Waschbusch, 2002), and more severe social functioning difficulties. In fact, ADHD comorbid with conduct problems is officially recognized as a separate condition by the International Classification of Diseases and Related Health Problems, 10th revision (ICD–10; World Health Organization, 2007) referred to as hyperkinetic conduct disorder (Banaschewski et al., 2003).
An estimated 30% to 50% of children with ADHD-IA may manifest characteristics such as hypoactivity, daydreaminess, lethargy, sluggish motor function, easy confusion, and slow processing speed, which have been deemed sluggish cognitive tempo (SCT) (Barkley, 2005; Barkley et al., 2001; McBurnett, Pfiffner, & Frick, 2002). These characteristics often co-occur with internalizing disorders such as anxiety or depression (Barkley, 2005; Carlson & Mann, 2002; Schatz & Rostain, 2006).
ADHD AND NEUROPSYCHOLOGY 11
As one can see, children with ADHD are a diverse population (e.g. Barkley, 2005; Hale et al., 2009a). Hence, an understanding of a child’s unique needs is essential to treatment efficacy. One implication is in terms of
pharmacotherapy. Though stimulant treatment has been shown to be a highly efficacious treatment for ADHD (Barkley, 2005; Zametkin & Ernst, 1999), approximately 10% to 20% of children with ADHD do not respond to stimulants (Greenhill, Halperin, & Abikoff, 1999). Children with comorbid anxiety, for example, may not be the best candidates for stimulant treatment, for stimulants often increase anxiety symptoms (Greenhill, Pliszka, & Dulcan, 2004). These children may respond better to selective serotonin reuptake inhibitors or SSRIs (Zametkin & Ernst, 1999), and may also benefit from cognitive behavioral therapy (Jensen et al., 2001; Kendall, 1994). Furthermore, differential effects of stimulant therapy have also been found based on ADHD subtype, with children with ADHD-CT demonstrating a more robust response than those with ADHD-IA (Hale et al., in press). Hale et al. (in press) found that within the inattentive group, those that had comorbid anxiety or depression were less likely to benefit from stimulant treatment than those with subthreshold hyperactive-impulsive symptoms.
A new approach to ADHD assessment.
Limitations of traditional behavioral assessment have fostered an interest in expanding the behavioral diagnosis of ADHD to include neuropsychological
factors. ADHD is now widely accepted to be a disorder of neuropsychiatric origin (Konrad, Gunther, Hanisch, & Herpertz-Dahlmann, 2004), largely due to advances in neuroimaging. Neuroimaging studies have primarily implicated abnormalities of the prefrontal cortex (Castellanos et al., 2002), which play a significant role in many of the symptomatic difficulties seen in children with ADHD (Nigg, 2006). Key regions include the dorsolateral prefrontal cortex (associated with working memory), orbital prefrontal cortex (inhibiting inappropriate actions), and anterior cingulate cortex (emotional and cognitive control). Due to these meaningful neurological findings, current research has extended the use of neuropsychological instruments to the assessment of ADHD (Barkley, 2005; Baron, 2004; Hale & Fiorello, 2004).
Neuropsychological testing has not yet been widely accepted as a routine part of ADHD evaluations (Barkley, 2005), and studies seeking to use these instruments to differentiate children with ADHD from controls have not found them to be diagnostic in their own right (Frazier, Demaree, & Youngstrom, 2004; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). In a meta-analysis of studies examining neuropsychological performance of children with ADHD, ADHD was best characterized by executive deficits in response inhibition, working memory, vigilance, and planning, with effect sizes in the medium range (Willcutt et al., 2005). However, a combined neuropsychological/behavioral approach may be of increased utility. Hale et al. (2009a) recently tested the utility
ADHD AND NEUROPSYCHOLOGY 13
of a psychosocial rating scale in combination with select neuropsychological measures of executive functioning and found that this battery correctly distinguished ADHD children from typical children at a rate of 87%.
The following chapter has four objectives: to (a) further discuss the presentation of ADHD with common comorbid conditions, (b) discuss the neuropsychology of ADHD and comorbid conditions, (c) discuss the impact of ADHD on neuropsychological processes, and (d) develop research questions.
Chapter 2 Literature Review
ADHD and common comorbid conditions.
Oppositional defiant disorder/conduct disorder. Comorbid ODD or CD
is found in 40% to 90% of children with ADHD (Pfiffner et al., 1999) and as previously stated, has also been proposed as a distinct subtype of ADHD (Barkley, 2005). ODD, which is often a precursor to CD, is characterized by patterns of defiant, negativistic, disobedient, and hostile behavior toward authority figures (APA, 2000). CD is distinguished from ODD by more serious violations of rules or the rights of others, such as physical aggression toward people or animals and theft. Children with comorbid ADHD and ODD/CD have increased difficulty with hyperactivity, impulsivity, and social skills (Turgay, 2005), as well as higher rates of teacher conflict and school refusal than those with ADHD or ODD alone (Harada, Yamazaki, & Saitoh, 2002). Children diagnosed with comorbid ODD or CD also report increased levels of anger compared to those only with ADHD, with those with ODD manifesting more verbal aggression and those with CD displaying more physical aggression (Hart, Miller, Newcorn, & Halperin, 2009).
Differential diagnosis is challenged by an overlap in the symptoms of ODD/CD and ADHD. Children with ADHD often exhibit impulsive,
ADHD AND NEUROPSYCHOLOGY 15
familial conflicts (Harada et al., 2002; Johnston & Marsh, 2001). Hence, it is easy to envision how ADHD symptoms such as failing to follow through on assignments and avoiding tasks that require sustained mental effort, failing to remain seated, blurting out answers, and Intruding on others could be interpreted by parents and teachers as oppositional or defiant. Additionally, viewing a child’s inattentive or hyperactive-impulsive behaviors as willful could result in power struggles that induce argumentativeness in a child (see Barkley, 1997b).
Anxiety and mood disorders. Comorbid anxiety disorders occur at a rate
of 30% in children with ADHD (National Resource Center on ADHD, 2003). GAD, which is characterized by a pattern of pervasive and excessive worry about a number of different aspects of life (APA, 2000), is the most commonly seen anxiety disorder in children with ADHD (Manassis, Tannock, Young, & Francis-John, 2007). Studies have found that the addition of anxiety to ADHD is
generally related to a worsening of outcomes. Those with this comorbidity have shown increased need for psychiatric treatment (Biederman et al., 1996),
increased school fears, panic, and mood disorders (Bowen, Chavira, Bailey, Stein, & Stein, 2008), decreased social competence (Biederman et al., 1996; Bowen et al., 2008) and decreased academic performance (Manassis et al., 2007). Older studies suggested that children with ADHD-IA were more likely to manifest internalizing disorders, such as anxiety or unipolar mood disorders, compared to the other ADHD subtypes (Biederman, Newcorn, & Sprich, 1991). However,
more recent studies suggest similar rates across ADHD subtypes (Acosta et al., 2008; Elia et al., 2008; Power et al., 2004).
A 10% to 30% comorbidity rate for mood disorders (depression) has been found in children with ADHD (National Resource Center on ADHD, 2003). Dysthymic disorder, a mild to moderate chronic depression (APA, 2000), co-occurs in ADHD children at the greatest frequency (Elia et al., 2008). Associated features of childhood depression can include school difficulties, school refusal, somatic complaints, aggression, negativism, withdrawal, and antisocial behavior (Spencer et al., 2007). Recent studies suggest similar rates of unipolar depression across ADHD subtypes (Acosta et al., 2008; Elia et al., 2008), while bipolar disorder has been associated more closely with ADHD-CT (Wilens, Biederman, & Wozniak, 2003) or ADHD-HI (Papalos & Papalos, 2006). Additionally, in those with ADHD-CT, males are more likely than females to develop major depressive disorder (Bauermeister et al., 2007).
Differentially diagnosing ADHD from internalizing disorders is
challenged by similarities in behavioral symptoms. For example, a child who has concentration difficulties due to an increased focus on anxious or depressive thoughts, as opposed to stimuli in the external environment, may simply appear inattentive to outside observers (Jarret & Olendick, 2008; Reddy & Hale, 2007). Additionally, hyperactivity-impulsivity may be assumed when a child is actually manifesting restless due to anxiety (psychomotor agitation) (Jarrett & Ollendick,
ADHD AND NEUROPSYCHOLOGY 17
2008; Nigg, Goldsmith & Sachek, 2004; Zametkin, & Ernst, 1999). Symptoms of childhood mania overlap greatly with those of hyperactivity-impulsivity, leading some researchers to posit that ADHD with hyperactivity may actually be an early developmental stage of bipolar disorder (see Papalos & Papalos, 2006). As previously discussed, an additional argument is that ADHD plus comorbid internalizing disorders may represent a distinct ADHD subtype (Barkley, 2005). Hale et al. (2010) posit that some children with ADHD-IA with comorbid anxiety or depression may actually have a type of “pseudo” ADHD characterized by different patterns of neuropsychological impairment than those with “true” ADHD.
Neuropsychology of ADHD.
The behavioral and cognitive dysfunction seen in individuals with ADHD arises from the interaction of multiple brain systems (Koziol & Budding, 2009), which is supported by findings from volumetric, activation likelihood estimation (ALE) and functional magnetic resonance imaging (fMRI) studies. ADHD is associated with an overall reduction in total brain volume that approximates 5% (Castellanos et al., 2002), with significant reductions having been found in the frontal lobes, basal ganglia (Castellanos et al., 1996), and the cerebellum (Valera, Faraone, Murray, & Seidman, 2007). Significant grey matter reductions have been found in the right superior frontal gyrus, right posterior gyrus, and the basal ganglia bilaterally, as well as white matter reductions concentrated in the left
hemisphere anterior to the pyramidal tracts and superior to the basal ganglia (Overmeyer et al., 2001). Accordingly, children with ADHD demonstrate hypoactivity in the anterior cingulate, dorsolateral prefrontal, inferior prefrontal and orbitofrontal cortices, as well as in the basal ganglia and parietal cortices on tasks designed to isolate frontal regions (Dickstein, Bannon, Castellanos, & Milham, 2006). A reverse pattern of activation has been seen on tasks of response inhibition and interference tasks, where children with ADHD demonstrate a reliance on more posterior regions of the brain as compared to typical children, who activate more frontal regions, suggesting inefficient processing (Vaidya, Bunge, Dudukovic, Zalecki, Elliot, & Gabriel, 2005).
Prefrontal subcortical circuits, which facilitate anterior-posterior axis communication and involvement of subcortical structures, are believed to play a significant role in ADHD (Hale & Fiorello, 2004; Koziol & Budding, 2009; Nigg, 2006). These include the motor, oculomotor, dorsolateral, orbitofrontal, and the anterior cingulate circuits, which originate from various areas of the prefrontal cortex and then project to the striatum, globus pallidus, substantia nigra, and thalamus before looping back to the frontal cortex (Tekin & Cummings, 2002). These circuits work in concert with the neurotransmitters of dopamine, glutamate, and GABA, which serve modulatory, excitatory, and inhibitory functions,
ADHD AND NEUROPSYCHOLOGY 19
Integrity of the frontal subcortical circuits is important for everyday behavioral functioning, with dysfunction resulting in a variety of cognitive and/or behavioral disturbances (Hale & Fiorello, 2004; Koziol & Budding, 2009; Nigg, 2006; Tekin & Cummings, 2002). The dorsolateral, orbitofrontal, and anterior cingulate circuits in particular are important for self-regulatory functions (Nigg, 2006). Hale, Bertin, and Brown (2004) argue that children with ADHD likely experience dysfunction in one or more circuits, especially the dorsolateral circuit in ADHD-IA and the orbitofrontal circuit in ADHD-HI (as cited in Hale & Fiorello, 2004).
The motor circuit is important for procedural learning or learning of new motor routines, and the oculomotor circuit important in sustained visual attention and searching strategies (Koziol & Budding, 2009). The integrity of the motor circuit may be gauged through motor procedural learning tasks. Information regarding the integrity of the oculomotor circuit may be gained through pencil and paper copying or cancellation tasks (Koziol & Budding, 2009).
The dorsolateral circuit is believed to be important may in working memory, deliberate control of action (Nigg, 2006), and attention in the areas of selection and maintenance (Koziol & Budding). Dysfunction involving this circuit may also manifest as problems with executive functions such as
organizing, planning, monitoring, and changing behavior (Hale & Fiorello, 2004). Additionally, individuals may present as perseverative, easily distracted in the
absence of external prompting and structure, and inflexible in their reasoning styles (Tekin & Cummings, 2002). They may either appear apathetic due to difficulties in initiation or perseverative due to difficulties in shifting their thinking or focus. Most neuropsychological tests assess functions of the
dorsolateral circuit (Ardila, 2008; Koziol & Budding, 2009). Dysfunction of this circuit may manifest in poor performance on working memory, planning,
organizational (Lichter & Cummings, 2001), or attentional tasks (Koziol & Budding, 2009).
The orbitofrontal circuit is believed to be responsible for behavioral inhibition and impulse control (Hale & Fiorello, 2004; Koziol & Budding, 2009; Nigg, 2006). It assists in inhibiting responses to external distractions or
competing distractions (Koziol & Budding, 2009). Orbitofrontal dysfunction is characterized by difficulties with affect regulation, judgment, and social behavior (Koziol & Budding, 2009). Dysfunction may also manifest as euphoria or mania (Cummings & Miller, 2007), emotional lability, explosive anger, and
inappropriate response to social cues (Tekin & Cummings, 2002). Dysfunction of this circuit is not directly assessed by neuropsychological tests (see Koziol & Budding, 2009). Inferences about the integrity of this circuit are best made through observation or report of behavior.
The anterior cingulate circuit modulates persistence, motivation, and attentional control (Hale & Fiorello, 2004; Koziol & Budding, 2009; Nigg, 2006)
ADHD AND NEUROPSYCHOLOGY 21
and may also result in lack of creativity, apathy, or abulia (Tekin & Cummings, 2002). Dysfunction of this circuit is also not well assessed by current
neuropsychological tests (see Koziol & Budding, 2009). Koziol & Budding (2009) explain that individuals with anterior cingulate dysfunction who have relatively intact cognitive profiles can elude detection on traditional
neuropsychological tests. As a result, any signs of dorsolateral dysfunction may be overly attributed to psychological or emotional factors. Observations of behavior and self-report data may be valuable sources of information for assessing integrity of the anterior cingulate circuit.
The basal ganglia, cerebellum, and corpus callosum have also been implicated in the expression of ADHD (Nigg, 2006). Abnormalities of the basal ganglia are believed to influence motivation, emotion, motor control (Nigg, 2006), intention of motor actions (Koziol & Budding, 2009), and executive and cognitive functions (Nigg, 2006). Together with dopamine, dysfunction in this area may also be responsible for the hyporesponsiveness of ADHD children to rewards (Koziol & Budding, 2009). The cerebellum is likely involved in disturbances of motor timing or temporal processing, as well as behavioral regulation (Koziol & Budding, 2009). The corpus callosum assists in
coordination of hemispheric communication, which is necessary for the selection of appropriate cognitive actions (Banich, 1998).
Neuropsychology of common ADHD comorbidities.
Neuroimaging research on ADHD comorbid with anxiety/mood disorders or ODD/CD appears to be limited at this time. However, studies exist that have examined these conditions separately. Similar to studies on ADHD, the following findings on anxiety, mood, and ODD/CD identify significant neurological
differences between individuals with and without these disorders thus providing evidence for also considering anxiety, depression, and ODD/CD as
neuropsychological conditions.
Abnormalities in prefrontal and limbic regions have been identified in both anxiety and mood disorders. Anxiety disorders have been linked to hyperarousal of the prefrontal cortex (PFC) (Berkowitz, Coplan, Reddy, & Gorman, 2007; Krain et al., 2008; Monk et al., 2006), with an overactive fronto limbic circuit responsible for social fear (Veit et al., 2002). GAD in particular is characterized by overactivity of the PFC regions (Berkowitz et al. 2007).
Abnormal functioning has also been identified in the amygdala (McClure et al., 2007), orbitofrontal cortex (Rolls, 2004), and anterior cingulate cortex (Allman, Hakeem, Erwin, Nimchinsky, & Hof, 2001). Specific abnormalities in
individuals with mood disorders include functioning of the PFC, basal ganglia, cerebellum, and hippocampus/amygdala areas (Beyer & Krishnan, 2002; Caetano et al., 2005; Koziol & Budding, 2009; Steingard et al., 2002). Though amygdala dysfunction is found in both anxiety and mood disorders, the nature of this
ADHD AND NEUROPSYCHOLOGY 23
dysfunction is characterized by overactivity in anxiety and by blunted activity in depression (Thomas et al., 2001;Veit et al., 2002).
The neurological correlates seen in anxiety and mood disorders may result in a disruption of attention, especially as it relates to processing emotional stimuli. Selective attention biases toward threatening stimuli have been observed in
individuals with anxiety and mood disorders (Joormann, Talbot, & Gotlib, 2007; Ladouceur, Dahl, Williamson, Birmaher, & Casey, 2006; Richards, French, Nash, Hadwin, & Donnelly, 2007; Taghavi, Dalgleish, Moradi, Neshat-Doost, & Yule, 2003). A decreased sensitivity toward reward (Forbes et al., 2006) and a memory bias for negative information (Lim & Kim, 2005) have also be found in those with mood disorders.
Abnormalities in frontal and limbic regions have also been observed in subjects with ODD/CD or comorbid ADHD/ODD/CD. Children with CD have shown abnormal activation patterns in the frontal and parietal regions when performing attention/inhibitory tasks (Banaschewski et al., 2003, 2004). However, this activation did not differ from subjects with ADHD or those with comorbid ADHD/CD. In contrast, research that has compared boys with pure ADHD to those with pure CD/ODD on attention/inhibitory control tasks has found dissociable differences. Boys with CD have shown reduced activity in bilateral temporal-parietal areas, as well as the posterior cingulate gyrus during inhibition failures (Rubia et al., 2008). Subjects with ADHD only showed
activation in the posterior cingulate gyrus (Rubia et al., 2008). Additionally, when attention/inhibitory tasks were rewarded, subjects deactivation was seen in the paralimbic regions of the insula, hippocampus, anterior cingulate, and cerebellum in subjects with CD (Rubia et al., 2009). In contrast, boys with ADHD showed reduced activity in the prefrontal regions, regardless of whether the task was rewarded (Rubia et al., 2008; Rubia et al., 2009). Rubia and colleagues (2009) concluded that problems of sustained attention may be attributed to dysfunction of the orbitofrontal-paralimbic motivation network in individuals with CD, whereas those with ADHD have disruption of the ventrolateral frontocerebellar network.
Aggressive behavior, whether alone or comorbid with ADHD, appears to result in reduced sensitivity to threatening/negative stimuli. Decreased activation in the anterior cingulate circuit and amygdala is seen in boys with CD when viewing negative emotional material (Sterzer, Stadler, Krebs, Kleinschmidt, & Poustka, 2005). This pattern is also seen in those with comorbid ADHD. Antisocial behavior in general may be attributed to hypoactivity of the
frontolimbic circuit, which encompasses the orbitofrontal cortex, insula, anterior cingulate, and amygdala (Veit et al., 2002).
ADHD and neuropsychological processes.
Auditory-verbal. Auditory-verbal skills are associated with more
posterior brain functions and primarily left hemisphere involvement for tasks of crystallized knowledge, such as vocabulary (Hale & Fiorello, 2004). However,
ADHD AND NEUROPSYCHOLOGY 25
frontal involvement is still necessary, given that all cognitive functions are governed by executive processes (Hale & Fiorello, 2004; Hale et al., 2009b; Luria, 1973). Brain lesion studies have correlated poor performance on tests of verbal intelligence to lesions in the left hemisphere, with the left inferior frontal cortex particularly affected (Gläscher et al., 2009).
Children with ADHD manifest a higher incidence of receptive, expressive, and language processing disorders than children without ADHD (Tannock & Brown, 2009). They have been found to score lower in every verbal ability area as measured on the Wechsler Intelligence Scale for Children–Third Edition (WISC–III) than typical children (Andreou, Agapitou, & Karapetsas, 2005). Additionally, two subtests of verbal crystallized knowledge (Information and Vocabulary), along with Digit Span and Picture Completion, were found to reliably discriminate ADHD children from typical children (Assessmany, Mcintosh, Phelps, & Rizza, 2001). Other studies have found deficits in verbal fluency and inferential listening comprehension (McInnes, Bedard,
Hogg-Johnson, & Tannock, 2007). Children with ADHD tend to struggle with language tasks that involve executive functions, such as organizing and monitoring verbal responses (Purvis & Tannock, 1997). Methylphenidate treatment may facilitate improvements in higher-order listening comprehension skills in ADHD children through increased attendance to the salient details in spoken discourse (McInnes et al., 2007).
The interaction between language difficulties and ADHD is complex and may be bidirectional. Children who struggle with language may develop ADHD symptoms as a result of their learning frustrations (Andreou et al., 2005).
Alternatively, ADHD children may manifest language disorders because they do not attend optimally to language development opportunities. In the case of central auditory processing disorder, some scholars have posited that this condition and ADHD may be different forms of a unitary disorder (Riccio, Hynd, Cohen, Hall, & Molt, 1994). In contrast, Hale, Fiorello, and Brown (2005) argue that children who demonstrate attention problems as the result of auditory processing problems do not manifest true or primary ADHD. ADHD subtype may also be related to the development of language problems, for language difficulties in preschoolers have correlated significantly with impulsivity, whereas this relationship was not found for inattention (Geurts & Embrechts, 2008).
Visuospatial. Visuospatial processes are associated with right hemisphere
and posterior brain functions (Hale & Fiorello, 2004). These processes are generally not as impaired as executive processes, such as working memory (Mayes & Calhoun, 2006). Children with ADHD typically perform within the average range on tests of visuospatial reasoning such as block design and matrices tasks (Pendley, Myers, Brown, & Reagan, 2004), and compared to other cognitive processes, visuospatial skills are generally viewed as areas of strength for ADHD children (Mayes & Calhoun, 2006). However, given that frontallymediated
ADHD AND NEUROPSYCHOLOGY 27
executive functions govern all aspects of cognition (Luria, 1973), it is certainly feasible that executive deficits could affect visuospatial performance (Hale et al., 2009b). Silk and colleagues (2008) found that a progressive matrices task placed heavy demands on the prefrontal cortex, due in part to the need for visuospatial attention and mental manipulation (Silk, Vance, Rinehart, Bradshaw, &
Cunnington, 2008). Though no performance differences were found on the matrices task, ADHD children in this study showed decreased activation in the right dorsolateral prefrontal cortex, the posterior parietal lobe, and the temporal lobe compared to typical children.
A process analysis of the neuropsychological constructs needed to perform visuospatial reasoning tasks also revealed heavy executive demands (see Hale & Fiorello, 2004). In the case of block design tasks, for example, processes such as visual attention, working memory, planning/organizing, and self-monitoring are necessary. An examinee must visually attend to the details in the design to reproduce it correctly and then self-monitor performance for errors. Self-monitoring is used when an examinee regulates the speed the designs are constructed. Holding the target design in working memory and utilizing a planful/organized approach also facilitates faster performance. Visual neglect (particularly of the left hemispace) (Jones, Craver-Lemley, and Barrett, 2008; Sandson, Bachna, & Morin, 2000), deficits in visual-spatial working memory (Bedard, Martinussen, Ickowicz, & Tannock, 2004), and problems with
planning/organizing and self-monitoring have all been associated with ADHD (Willcut et al., 2005).
Processing speed. Generally defined, processing speed refers to the speed
at which different cognitive operations can be performed or executed (Reichenberg & Harvey, 2007). Speed of performance is related to the
frontostriatal system (Rabbitt et al., 2007), and as tasks become more automatic, decreased cortical activity is seen in regions such as the dorsolateral prefrontal cortex in exchange for increased activity in subcortical regions such as the basal ganglia (Koziol & Budding, 2009; Saling & Phillips, 2007). However,
individuals who perform tasks more slowly sustain this pattern of cortical activity (Saling & Phillips, 2007), thus suggesting the need for increased concentration and cognitive control than those who perform tasks quickly (Koziol & Budding, 2009).
Processing speed tasks are multifaceted, in that different
neuropsychological processes/neuroanatomical networks are engaged depending on the nature of the task (Koziol & Budding, 2009). For example, the Coding and Symbol Search subtests from the Wechsler Intelligence Scales differ in that the Coding subtest places greater demands on working memory, whereas the Symbol Search subtest places more emphasis on perceptual discrimination (Koziol & Budding, 2008). Further evidence is provided by Gläscher and colleagues (2009) who were unable to localize the Processing Speed Index from the Wechsler Adult
ADHD AND NEUROPSYCHOLOGY 29
Intelligence Scale (WAIS) to any one area of the brain. Activation was found across various frontal and parietal regions of both hemispheres. Symbol Search overlapped to a greater degree with Perceptual Organizational subtests on the WAIS, while the Coding subtest overlapped with locations of Verbal
Comprehension and Working Memory. An additional neuroimaging study of the Symbol Search subtest showed that subjects activated regions of the occipital, parietal, temporal, and dorsolateral prefrontal cortexes (Sweet et al., 2005).
Measures of processing speed have shown significant promise in differentiating ADHD children from typical children. As compared to typical children, children with ADHD have shown significantly decreased processing speed scores on the Wechsler scales (Calhoun & Mayes, 2005; Elk et al., 2007; Mayes & Calhoun, 2004; Mayes & Calhoun, 2007a), with lower performance found on the Coding subtest than the Symbol Search subtest (Calhoun & Mayes, 2005). Lower processing speed also appears to reliably differentiate ADHD children from those with mental retardation, ODD, and anxiety disorders. However, a lower processing speed has also been found in children with autism, bipolar disorder, unipolar depression, and learning disabilities (Calhoun & Mayes, 2005).
Studies that have differentiated between ADHD subtypes on measures of processing speed have yielded mixed results. Chhabildas, Pennington, and Willcutt (2001) found that combined and inattentive groups both demonstrated
deficits in processing speed that were not seen in the hyperactive-impulsive group. Other research groups have found that children with inattentive type ADHD perform significantly worse on processing speed tasks as compared to those with combined type (Mayes, Calhoun, Chase, Mink, & Stagg, 2009; Solanto et al., 2007). The conflicting findings between these two studies may be
attributed to the different definitions of processing speed of each research group. As previously discussed in this section, different processing speed tasks engage different neurological networks (Koziol & Budding, 2009). Mayes et al. (2009) and Solanto et al. (2007) used the same measures that will be used in the
proposed study.
Working memory. Working memory refers to the capacity to mentally
manipulate information placed in immediate storage (Miller, 2007), and is likely primarily a function of the dorsolateral prefrontal cortex (Levy & Goldman-Rakic, 2000). Working memory facilitates the activation of many neurocognitive processes (see Hale & Fiorello, 2004) and has been equated with self-directed speech, (Barkley, 2005), which permits children to reflect on events, question their actions, plan, problem solve, utilize metacognition, and follow directions (Dawson & Guare, 2004). Additionally, internal dialogues facilitate self-regulation of motor and emotional responses (Barkley, 2005). Furthermore, working memory is closely intertwined with attention (see Barkley, 2006; Baron, 2004), because irrelevant stimuli must be ignored when performing working
ADHD AND NEUROPSYCHOLOGY 31
memory tasks (Nigg, 2006).
Tests of working memory, such as digit span tasks, have been consistently found to reliably differentiate ADHD children from typical children (Assessmany et al., 2001; Elk et al., 2007; Mayes & Calhoun, 2002, 2007a, 2007b). The degree of working memory impairment found in children with ADHD is even greater on tasks of spatial working memory than those of verbal working memory (Willcutt et al., 2005). However, the less robust finding of verbal working memory may be due in part to the common approach of not considering forward and backward versions of digit span tasks separately (Hale, Hoeppner, & Fiorello, 2002). Digits backward measures attention and executive function processes and is associated with dorsolateral prefrontal involvement, whereas digits forward measures short-term auditory memory associated with left hemisphere auditory-verbal processes (Hale et al., 2002). While working memory measures have been found to
discriminate ADHD children from typical children, as well as those with anxiety, depression, or ODD, results are similar for children with autism and learning disabilities (Mayes & Calhoun, 2004, 2007a;). Studies that have examined working memory performance by ADHD subtype have found no significant differences between inattentive and combined groups (Mayes & Calhoun, 2009; Solanto et al., 2007).
Sustained attention. Sustained attention is defined as an individual’s
models of sustained attention implicate interaction of cortical (frontal, prefrontal, parietal) and subcortical structures (limbic system, basal ganglia), as well as ascending and descending pathways between the basal ganglia, frontal lobes, and thalamus (Riccio, Reynolds, Lowe, & Moore, 2002). These models have been supported by neuroimaging data (Riccio et al., 2002).
Continuous performance tests (CPTs) are frequently utilized to assess the construct of sustained attention and have shown sensitivity to neurological impairment/damage (Riccio et al., 2002). CPTs exist in various formats, such as auditory and visual. One popular version is the Conners’ Continuous
Performance Test, which is a computerized measure that requires the examinee to press the spacebar in response to visual stimuli displayed at varying speeds on a computer screen. This instrument yields measures of inattention, impulsivity, and vigilance (Conners & MHS Staff, 2004).
CPTs are most commonly utilized to assist in evaluating children for ADHD and to determine stimulant therapy response (Barkley, 2005; Conners & MHS Staff, 2004). A meta-analytic review of CPT research found that children with ADHD manifest higher error rates of omission (failure to respond to targets) and commission (responding to non targets) (Losier, McGrath, & Klein, 1996). They also show increased difficulties distinguishing between targets and non targets (signal detection). Performance measured by commissions, omissions, and
ADHD AND NEUROPSYCHOLOGY 33
signal detection has been shown to improve in ADHD children treated with methylphenidate.
Though some ADHD subtype differences have been found on CPTs, these instruments have shown limited specificity for distinguishing among the different forms of ADHD. Some studies suggest that children with ADHD-CT tend to demonstrate greater impulsivity than those with IA (Solanto et al., 2007), and children with ADHD-IA and CT tend to have slower reaction times than those with HI (Querne & Berquin, 2009). However, research that has directly compared DSM–IV symptoms to performance variables on the Conners’ CPT found that the combination of increased overall omission and commission errors, as well as of omission errors as the test progressed, was related to almost all of the 18 ADHD symptoms in the DSM–IV (Epstein et al., 2003). Hence, Epstein and colleagues concluded that the CPT is a good general measure of ADHD rather than ADHD subtype.
Despite the popularity of utilizing CPT measures in the assessment of ADHD, they may also be of value in assessing other psychiatric conditions where attention is impaired (Riccio et al., 2002). In a review of CPT studies, Riccio and colleagues (2002) concluded that CPTs demonstrate sensitivity to attentional system dysfunction, whether the damage to neurological attention systems was diffuse or focal. Thus, CPTs more accurately identify attentional disturbance rather than specific conditions such as ADHD. For example, learning disabilities
(Advokat, Martino, & Gouvier, 2007), schizophrenia (Nieuwenstein, Aleman, & de Haan, 2001), and major depression with psychosis (Nelson, Sax, Strakowski, 1998) have all been linked to abnormal CPT performance.
Neuropsychological processes in ADHD plus comorbid conditions.
There appears to be a paucity of research that has examined
neuropsychological performance in ADHD with comorbid conditions such as anxiety, depression, or ODD/CD. Of the existing studies, mixed results for meaningful group differences have been found. It has been suggested that neuropsychological differences are similar for children with ADHD compared to those with comorbid anxiety, depression, or CD (Klorman et al., 1999; Seidman et al., 1995). Related to verbal processes, one study found lower verbal intelligence in children with comorbid CD (Waschbusch, 2002). No studies could be located related to visuospatial processes. Some evidence exists that working memory may be more impaired in ADHD children with comorbid anxiety (Schatz & Rostain, 2006) and also less amenable to improvements with methylphenidate treatment (Bedard & Tannock, 2008; Tannock, Ickowicz, & Schachar, 1995). However, Mayes et al. (2009) found that the addition of comorbid anxiety or depression did not account for further declines in working memory or processing speed performance. Rucklidge (2006) found processing speed deficits in children with ADHD/bipolar disorder, but these were less severe than those seen in
ADHD AND NEUROPSYCHOLOGY 35
to further decrease working memory (Mayes et al., 2009; Thorell & Wåhlstedt, 2006) or processing speed (Mayes et al., 2009).
More research has been conducted on ADHD comorbidities in the area of sustained attention/response inhibition. Studies examining comorbid anxiety or depression have provided mixed support for performance deficits that differ from those in individuals who have ADHD without comorbidity. Children with ADHD/anxiety have shown response inhibition deficits, but these deficits did not remain once ADHD was factored out (Korenblum, Chen, Manassis, & Schachar, 2007). Other studies have suggested that comorbid anxiety may offset
impulsivity/response inhibition deficits (Manassis, Tannock, & Barbosa, 2000; Schatz & Rostain, 2006). However, this effect may vary based on the nature of anxiety, with physiological anxiety serving to increase response inhibition and cognitive anxiety serving to decrease response inhibition (Epstein, Goldberg, Conners, & March, 1997). A study conducted with adults with ADHD comorbid with depression found that this group performed slightly worse on a sustained attention task than those with ADHD alone (Riordan et al., 1999). Some studies examining comorbid bipolar disorder suggest that this comorbidity leads to increased impairment on CPT tasks (Rucklidge, 2006), while others have
suggested that performance is similar between ADHD/bipolar and ADHD groups (Adler et al., 2005).
with ADHD/ ODD/CD have also yielded mixed results. ADHD comorbid with ODD/CD may increase impulsivity (Banaschewski et al., 2004; Matier, Halperin, Sharma, Newcorn, & Sathaye, 1992; Newcorn et al., 2001), an effect that is not remediated by methylphenidate treatment (Matier et al., 1992). However, another study that found boys with comorbid CD outperformed those with ADHD alone on a CPT task (Banaschewski et al., 2003).
Research problem and limitations of past research.
The diagnosis of ADHD can be a complex process. Traditional behavioral diagnosis is complicated by factors such as interrater disagreement (Angtrop et al., 2002; Bird et al., 1992; Grills & Ollendick, 2002), high comorbidity rates (National Resource Center on ADHD, 2003) and shared symptomatology among different psychiatric disorders (Hale et al., 2001; Mahone et al., 2002; Sullivan & Riccio, 2007). Due to these complexities and mounting evidence of neurological differences in children with ADHD, many researchers have turned to the use of neuropsychological instruments to aid in the diagnostic process. While
performance trends have been discovered, the sole use of neuropsychological instruments has not proven diagnostic of ADHD (e.g. Barkley, 2005; Frazier et al., 2004; Willcutt et al., 2005). In contrast, fewer studies have utilized a combined behavioral/neuropsychological approach, which has proven more sensitive in diagnosing ADHD (Hale et al., 2009a). The present study was intended to add to the research base on whether a combined
ADHD AND NEUROPSYCHOLOGY 37
neuropsychological/behavioral approach can be of value in the diagnosis of ADHD. Additionally, comorbid conditions and ADHD subtype were considered, which represented further strengths as compared to past literature. Furthermore, all were free of psychotropic medication at time of assessment, a confound in many past studies that have examined attentional processes (Ottowitz, Dougherty, & Savage, 2002).
Many neuropsychological instruments that have shown promise in the evaluation of children with ADHD are generally reserved for practitioners with specialized training in neuropsychological assessment (Miller, 2007). In contrast, the present study utilized the Wechsler Intelligence Scale for Children–Fourth Edition (WISC–IV; Wechsler, 2003) and Conners’ Continuous Performance Test– Second Edition (CPT–II; Conners & MHS Staff, 2004), two instruments
commonly used by psychologists with generalist training. Though the WISC is traditionally utilized for the diagnosis of learning disorders or cognitive
impairments (see Sattler, 2001) and the CPT is used to supplement behavioral data in ADHD evaluations (Barkley, 2005), these instruments have both shown sensitivity in identifying neurological impairment (Belanger, Curtiss, Demery, Lebowitz, & Vanderploeg, 2005; Hale et al., 2002; Mayes & Calhoun, 2004; Riccio et al., 2002). Furthermore, profile differences have been found in children with ADHD on WISC and CPT assessments (Calhoun & Mayes, 2005; Losier et al., 1996; Mayes & Calhoun, 2004, 2006, 2007a, 2007b).
The present study explored the behavioral and neuropsychological patterns found in children with ADHD children and those with comorbid conditions, as well as the utility of a combined neuropsychological/behavioral approach in differentiating among ADHD groups. The groups of focus in the present study included ADHD-IA, IA comorbid with an internalizing disorder (IA + INT), CT, and CT comorbid with an externalizing disorder (CT + EXT). The comorbid groups were chosen on the basis of past research that suggests that ADHD IA + INT and CT + EXT may represent distinct ADHD subtypes (Angold, Costello, & Erkanli, 1999; Barkley, 2005; Jensen et al., 2001; Stefanatos & Baron, 2007).
Using assessment data derived from mental health clinics within the midwestern and northeastern United States, subject performance was analyzed based on scores from the WISC-IV, CPT-II, and the Achenbach System of Empirically Based Assessment Child Behavior Checklist (ASEBA CBCL) and Teacher Report Form (TRF) (Achenbach & Rescorla, 2001). The following specific research questions were explored: (a) Do different neuropsychological and behavioral patterns, as measured by the WISC-IV, CPT-II, CBCL, and TRF exist in the different ADHD subgroups; and (b) Can the neuropsychological (WISC-IV and CPT-II) and behavioral (CBCL and TRF) variables discriminate between the ADHD groups with and without comorbid internalizing and
ADHD AND NEUROPSYCHOLOGY 39
The research questions of this study were exploratory in nature. Hence, no directional hypotheses were developed. However, diverse findings were expected to emerge among the ADHD subgroups on all measures utilized, and the WISC– IV, CPT–II, CBCL, and TRF variables were expected to reliably differentiate between the subgroups. Furthermore, the results of this study were expected to further illustrate the heterogeneous nature of ADHD (Barkley, 2005; Hale et al., 2009a) and support the utility of a combined behavioral/neuropsychological approach in the diagnosis of ADHD (Hale et al., 2009a), as opposed to one that relies on neuropsychological or behavioral measures alone.
Chapter 3 Method
Subjects.
All subjects in the present study were drawn from three different clinics within the midwestern and northeastern U.S. All had previously received comprehensive ADHD evaluations, which included the WISC–IV (Wechsler, 2003), CPT–II (Conners & MHS Staff, 2004), CBCL (Achenbach & Rescorla, 2001), as well as a semi structured interview and a behavior rating scale designed to measure ADHD. Many assessments also included the TRF, though it was not necessary for subject selection. Diagnosis of ADHD was rendered by licensed psychologists based on clinical evaluation and clinic ADHD rating scales (not the CBCL/TRF). To control for intellectual deficits that could potentially confound results, only children with full scale ability standard scores ≥75 were selected.
Additionally, potential subjects who were taking any kind of psychotropic medication at the time of testing and those who had a known traumatic brain injury or a medical condition that may affect psychological functioning (e.g., epilepsy) were excluded. Subjects were not eliminated from the analysis due to a comorbid learning or language disorder.
The total sample consisted of 85 children ranging between the ages of 6 and 16 (Sample A). From the total sample, subjects whose files contained all necessary information were then divided into IA (n = 18), IA + INT (n = 8), CT (n
ADHD AND NEUROPSYCHOLOGY 41
= 25), and CT + EXT (n = 12) groups to examine the research questions of the present study. This resulted in a total sample size of 63. Because many subjects in Sample B had ASEBA TRF results in addition to the required ASEBA CBCL results, a third sample was later formed for advanced analysis (Sample C, n = 42).
Several criteria were used to form the IA, IA + INT, CT, and CT + EXT subgroups, which were used in the statistical analyses of samples B and C. Due to small sample size, subjects classified as having ADHD-NOS were included in the IA groups and those with HI were included in the CT groups, which could be consistent with neuropsychological characteristics of these ADHD subtypes (Hale et al., 2009). According to the DSM–IV (APA, 2000), ADHD-NOS often is reserved for individuals demonstrating characteristics of sluggishness,
daydreaming, and hypoactivity. These characteristics have been deemed sluggish cognitive tempo, which research suggests may be a subset of the IA category (Barkley, 2005; Barkley et al., 2001, McBurnett et al., 2002). Additionally, CT may present as HI in its earlier stages or at younger ages (Barkley, 2005).
Further criteria were used to determine subject membership in the comorbid groups (IA + INT and CT + EXT). Because full criteria for a DSM
disorder were not met, not otherwise specified (NOS) comorbid disorders (e.g. DRB NOS, Anxiety NOS, etc.) were not recognized as comorbid conditions. CT subjects with a comorbid internalizing disorder (including those with an
